ugs.py 文件源码

def table_log_likelihood(self):
        log_likelihood = 0.
        for document_index in xrange(self._D):
            log_likelihood += len(self._k_dt[document_index]) * numpy.log(self._alpha) - log_factorial(len(self._t_dv[document_index]), self._alpha)
            for table_index in xrange(len(self._k_dt[document_index])):
                log_likelihood += scipy.special.gammaln(self._n_dt[document_index][table_index])
            log_likelihood += scipy.special.gammaln(self._alpha)

        return log_likelihood